Channel Sequence Metrics for Fast-Varying Data Transmission
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Solution Overview
Problem
Existing data transmission methods are complex and require significant effort to handle multiple sources of interference in transmission channels, resulting in low data rates and impractical implementation, especially when the channel properties are unknown.
Innovation Solution
A method for determining a selection metric for character strings based on hypothetical channel sequences, which calculates the sum of differences between consecutive channel coefficients to select the most plausible character string from a received character string, even with unknown and multi-parameter channel sequences, using a low-complexity approach suitable for various transmission channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex reception or detection methods are used to handle multiple interference sources, then the ability to deal with errors from multiple sources is improved, but the device complexity and execution effort increase significantly
Solution Approach 1:
The patent segments the channel characteristics into discrete states and uses segmentation of the received signal into N symbols. By dividing the complex problem of handling multiple interference sources into manageable segments (discrete channel states and symbol groups), the system can process each segment independently using simple operations, avoiding the need for complex overall processing while maintaining reliability.
Solution Approach 2:
The patent changes the parameter representation from continuous channel coefficients to discrete channel states. By quantizing the channel characteristics into a finite number of states and using parameter changes in the form of discrete state transitions, the system simplifies the reception method while maintaining the ability to handle multiple interference sources through state-based processing.
2Reliability
If complex reception or detection methods are used to handle multiple interference sources, then the error correction capability is improved, but the achievable data rate decreases due to increased execution time
Solution Approach 1:
The patent performs preliminary action by pre-defining discrete channel states and their transition probabilities before actual data reception. The receiver prepares a trellis structure and pre-calculates metric values for each state transition based on received symbols. This preliminary setup enables rapid error correction during actual data transmission without requiring complex real-time computations, thus maintaining high data rates while improving reliability.
3Adaptability or versatility
If methods are used for channels with unknown transmission properties, then the adaptability to unknown channels is improved, but the computational effort increases
Solution Approach 1:
The patent implements self-service by enabling the receiver to autonomously adapt to unknown channel conditions through self-organizing state transitions. The discrete hidden Markov model allows the receiver to automatically learn and track channel state changes based on received symbols without requiring external channel characterization or complex adaptive algorithms. The system serves itself by using the received signal structure to infer channel properties, reducing computational effort while maintaining adaptability.
Data Source
AI summary
The present invention relates to a method for determining a selection metric for a selection of a character string (sN) from a plurality of permissible character strings (sN) of a character string alphabet (110) based on a character string (150) received via a transmission channel (160), the plurality of permissible Character strings (sN) is specified by a character string alphabet (110) and each character string (sN) has a plurality N of information units (125). The method has the following steps: determining a hypothetical channel sequence (hN) based on the received character string (150) and each character string (sN) of the plurality of permissible character strings from the character string alphabet (110), the hypothetical channel sequence (hN) having a plurality N of hypothetical channel coefficients (h[n]), which are each assigned to an information unit (125) and determining the selection metric for each hypothetical channel sequence (hN) as the difference between two successive hypothetical channel coefficients (h[n], h[n+1] ) of a hypothetical channel sequence (hN). The method enables a receiving unit to select a character string from a character string alphabet in a manner that is not complex, requires little computational effort, and is reliable in the case of a plurality of different and previously unknown sources of interference and interference on the transmission channel